空天防御2025，Vol.8Issue(6)：25-34,10.
基于多视角互学习网络的遮挡SAR目标识别
Occluded SAR Target Recognition Based on Multi-View Mutual Learning Network
摘要
Abstract
For the problem of SAR target recognition in occluded scenarios,this paper proposes a novel method called the multi-view mutual learning network.The proposed method is a mutual learning framework consisting of a multi-view complementary feature learning network and a recognition network,which aims to improve the recognition model's feature extraction ability through knowledge interaction at the feature level.Specifically,to enhance the recognition network's feature extraction ability,this study developed an attribute-scattering-center-guided hierarchical feature extraction method.In view of the implementation challenges with target features in occluded scenarios,a multi-view complementary learning method was employed to comprehensively characterize target features by leveraging complementary features across different SAR images at adjacent azimuth angles.Contrastive experimental results on the MSTAR dataset show that the proposed method performs well across varying levels of occlusion.关键词
合成孔径雷达/遮挡目标识别/多视角互学习网络/属性散射中心Key words
synthetic aperture radar/occluded target recognition/multi-view mutual learning network/attribute scattering center分类
航空航天引用本文复制引用
任浩浩,崔闪,蒋欣妤,梁纾饴,周云..基于多视角互学习网络的遮挡SAR目标识别[J].空天防御,2025,8(6):25-34,10.基金项目
国家自然科学基金项目(62201124) （62201124）
中国航天科技集团有限公司第八研究院产学研合作基金项目(SAST2023-008) （SAST2023-008）
